1. Field of Invention
This disclosure relates to the radar and Electronic Warfare Support Measures (ESM) systems located on a single aircraft. In one embodiment, the disclosure utilizes infrequently scheduled radar inputs to an otherwise passive ESM target tracking filter to enhance the performance of the passive tracker while minimizing the chance the radar is detected by ESM or Radar Warning Receivers (RWR) on other platforms.
2. Description of Related Art
FIG. 1 shows a typical conventional installation of the ESM and radar systems on tactical aircraft. In such installations the active detection system (represented by radar 105) and the passive detection system (represented by antenna pairs 108, 109) are essentially separate, as shown. Both systems have tracking filters 100 and 101. The inputs to the radar tracking filter 100 are target azimuth a, range r, and if the radar measures Doppler, radial rate {dot over (r)}. Hence, the input to the active detection radar system is either the vector 102 or 103. The input to passive detection system filter 101 is the scalar azimuth or bearing a 104. Hence, this filter is called a bearings-only estimator.
These filters are typically used to track targets at different ranges. The reflected signal power the radar works with is proportional to 1/r4 while the direct path power the ESM receiver detects is proportional to 1/r2. So often in conventional systems the trackers are employed in a complementary manner, with the ESM tracker used mostly for distant emitters and the radar tracker for close-in targets. But there are also tactically important situations where the ESM tracker is used close-in to avoid threat intercept receivers, i.e., 111 located on other aircraft, detecting the radar, and hence the presence of ownship. Thus, an embodiment of the disclosure is concerned with this overlap region, where the radar can detect the emitter, but it is advantageous to use passive, bearings-only tracking.
In addition to detection avoidance, there are other benefits to bearings-only tracking. The ESM tracker has a field of view (FOV) advantage over the radar. To detect targets and subsequently measure azimuth and obtain range information the radar electronically or mechanically steers its antenna 105. This maximizes pattern gain in different angular directions to compensate for the 1/r4 loss, but can only be done within a restricted FOV 106. By contrast, the ESM system measures signal angle of arrival (AOA) using passive interferometers, for example 1071. Although an interferometer has at most a ±90° FOV, nearly 360° coverage is achieved by switching 121 between several antenna pairs such as 108, 109 to create additional long baseline interferometers or LBI, e.g., 1072, around the aircraft.
But while the bearings-only ESM target estimator 101 can track emitters at any relative bearing and at ranges several times further out than detectable by the radar, there its advantage over the radar tracker 100 ends. It ends because recursively estimating target position and velocity from the single azimuth input 104 is much less straightforward than estimating kinematics from the vector inputs 102 and 103.
A problem in bearings-only estimation is a sequence of bearing measurements cannot be uniquely associated with the correct emitter position and velocity without the observer undergoing special accelerations. That is, as described by Fogel and Gavish in “Nth-Order Dynamics Target Observability from Angle Measurements”, IEEE Transactions on Aerospace and Electronic Systems, AES-24, 3 (May 1988), conventional bearings-only passive emitter tracking requires the observer to maneuver during the sequence of receiver dwells used to collect the angle measurements. The special maneuver required depends on the target motion, and in particular not just its velocity, but various higher order derivatives of its velocity. Of course, since the target's motion is not known beforehand, neither is the observability maneuver required.
Because the observability maneuver is not known, it is common for the ESM tracker design to incorporate the unwarranted a priori assumption the target is flying a constant velocity track requiring, according to Fogel and Gavish, the observer to fly two constant velocity legs on different headings. Thus prior methods of bearings-only target tracking, e.g., as described by U.S. Pat. No. 5,877,998 Aidala, et al. in “Recursive Method for Target Motion Analysis,” emphasize such observer motion. But then even if the emitter happens to indeed be flying a constant velocity track, convergence to a range estimate occurs only after the observer completes the first leg and turns. That is, the target is located only after the second leg has begun. Hence, Aidala notes it is an object of its invention “to provide an improved method . . . for providing range estimates as soon as two measurement legs of data become available.”
The emitting aircraft may be flying any of a host of missions. These missions each involve special flight regimes such as cruise, loiter, supersonic dash and missile launch. Some regimes incorporate long constant velocity legs but all also require heading changes and other accelerations. So the chance that a significant number of detected emitters will be at constant velocity throughout the initialization phase is small. This leads to the frequent failure of bearings-only estimators to initialize correctly and prevents their subsequent convergence to the true target track. Further, even when they do converge the target is likely to subsequently undergo an acceleration that causes a constant-velocity estimator to break track or diverge.
Techniques exist addressing the track divergence problem. One example is Applicant's patent application Ser. No. 11/637,702, filed Dec. 13, 2006, now abandoned, and entitled “Method and Apparatus for Tracking a Maneuvering Emitter Utilizing Reduced Order State Estimators”. According to an embodiment, the disclosure allows a bearings-only estimator with a constant velocity core model to track targets through various maneuvers.
FIG. 3 illustrates the performance of the so-called “Reduced Order” adaptive method using flight test data obtained in experiments carried out by the Electronic Systems Division of Northrop Grumman Corporation. FIG. 2 shows the tracks flown to generate bearing measurement data. To describe the reduced order adaptive method, reference is made simultaneously to FIGS. 2 and 3. Referring to FIG. 2, aircraft 200 is the observer and aircraft 201 is the emitting or target aircraft. Before observer aircraft 200 (ownship) turns at 202, the ESM estimator “floats” 301 (see FIG. 3) at a fictitious range of about 100 nmi. After the turn, the estimator enters a transient phase 302 where it begins convergence. The convergence phase last for over 20 seconds until at 303 target aircraft 201 maneuvers 203. A conventional tracking filter would diverge at this time, but the adaptive feature of the estimator allows re-convergence 304. The filter then follows 305 the target track through subsequent target maneuvers 204 and 205.
FIG. 4 shows the range accuracy achieved of FIGS. 2 and 3. Because of the target maneuver during the transient state, convergence took 50 seconds after the observer's first turn, i.e., it ended about 70 seconds after the track was initiated at point 400. Thereafter, the range accuracy averages 5% despite maneuvers (401) that would have caused conventional estimators to break or lose track.
It is possible to shorten the initial convergence time and mitigate the onerous observer maneuver requirement using the Applicant's disclosure entitled: “Method of Passively Estimating an Emitter's Position and Velocity Using Bearings-Only without Requiring Observer Acceleration”, issued as U.S. Pat. No. 6,714,155 (“the '155 patent). According to one embodiment of the '155 patent, a set of possible ranges and corresponding velocities is generated for an emitter without an observer heading change. This is done, in part, by identifying the emitting aircraft's flight regime from radar parameters measured by the ESM system. This information, coupled with bearing rate measurements, provides a set of possible ranges and velocities. Hence the method ameliorates the observability problem but does not typically solve it with a unique initial target state. After convergence the track accuracy would still average 5%.
Although excellent for a bearings-only estimator tracking maneuvering targets, 5% accuracy is poor compared to that achieved by the active radar tracker 100 (FIG. 1). The radar can track a target with an error measured in meters rather than kilometers. Further, the target's motion is immediately observable from the measurement set 102 or 103. No ownship maneuver is required for the tracker to converge, although the aircraft may still have to maneuver to keep the target within the restricted FOV 106.
Since radar receiver 119 may receive multiple returns in a single burst from transmitter 120, complex processing is required to establish a radar track. In a typical sequence, Mode Controller 115 establishes a search mode, then an acquisition mode and finally a track mode.
The radar detects new targets in search mode by scanning spatial volumes. The scanning is done by electronically or mechanically steering the gain of the highly directional antenna or array 105, periodically revisiting a set of relative azimuths and elevations. Returns are filtered scan-to-scan to remove stationary or slow moving reflections by utilizing either incoherent or coherent moving target indicator (“MTI”) processing. This processing occurs at signal processor 118 of FIG. 1.
Most remaining returns belong to moving targets. These returns undergo associative processing to initiate target tracks in an acquisition mode. Logic checks reasonable kinematic limits on subsequent scans, eventually either confirming a tentative track as valid or rejecting it. The successfully-promoted target then enters a dedicated track mode, with its position, velocity and possibly higher order kinematics updated by radar target tracker (interchangeably, target filter) 100.
In the initial search or scan mode the time between target tracker updates depends on the antenna gain steering. For example, if the scan revisits the target's spatial volume 4 times a second, the tracker update will average 4 Hz. In the dedicated track mode a phased array radar can time share a single beam among several targets, allowing very rapid tracker updates. Thus, the estimator updated at 4 Hz in scan may be updated at 16 Hz or faster when in track mode.
Unfortunately for the radar, this well-established scan, acquisition and track mode behavior is exploited by ESM systems on other platforms to detect it and passively range its location. Hence, radar pays a price for its excellent trajectory estimation capability. The threat's ESM system implements a tuning strategy based on knowledge of radar modes to assure the receiver 111 scanning in frequency is able to intercept a spatially scanning transmitter within an acceptable time. That is, the ESM system design addresses and solves the scan-on-scan mean time to intercept (“MTTI”) problem. In solving this problem there is a trade off between false alarms, i.e., detections triggered by noise and MTTI. To assure a radar was detected, typically several sequential detections on subsequent closely spaced dwells are required. It is critical to avoid spurious detections or false alarms. These seriously impact the ESM system's ability to detect new emitters.
Understanding the extremely deleterious effect of false alarms requires understanding ESM parameter extraction. For example, once a radar is detected pulse parameter measurements type or “fingerprint” it in process 112. These parameters are then stored in Active Emitter File (AEF) 114 and subsequently used to sort new detects from old in process 113. An example parameter used in such sorting is the pulse repetition interval or PRI. Obtaining parameters like PRI requires collecting many pulses with an extended dwell. That is, receiver 111 must tune to one fixed frequency for a comparatively long time. However, sitting on one frequency impacts detecting new emitters and hence MTTI. Extended dwells are only scheduled after the emitter has been detected in more than one dwell to ensure the probability of false alarm is near zero.
Emitter parameter measurements provide vital information about the radar's mode. This in turn provides extremely valuable insight into the threat's intent and hence flight regime. For example, the '155 patent utilizes this information in determining possible initial emitter range, speed and headings. Another critical use is determining if ownship is in danger. For example, U.S. Pat. No. 7,148,835 to Bricker, et al. and entitled: “Method and Apparatus for Identifying Ownship Threats” determines whether the observer is engaged by a radar in track mode, possibly as a preliminary to the threat launching a missile.
In summary, ESM systems are excellent for fingerprinting radar systems and assessing their intent. But ESM passive emitter tracker performance is fragile and uncertain because it is impacted by initialization, convergence and track maintenance problems. Even when passive trackers converge to the correct track, the resulting errors are large compared to active radar estimators.
Radar systems do a superb job accurately tracking targets. They achieve their accuracy by measurements involving range information as well as azimuth and by further implementing special operational modes. These modes ultimately generate the very rapid measurement updates needed to closely follow targets through maneuvers.
But as a consequence, the radar also provides copious quantities of data to threat ESM systems. ESM systems extract parameters from this data. These parameters establish the state of the radar and particularly its mode of operation (e.g., search, acquisition or track). This information is then used to neutralize the radar with defensive flight maneuvers and Electronic Counter Measures (ECM).